- Presentation Slides
- Replication Package
- ESLint Custom Analyzer
- Static Analysis Data
- Runtime Analysis Data
Authors:
- Georgios Panormitis Latos
- Joey Karlsson
Supervisor: Farnaz Fotrousi
University: University of Gothenburg.
Date: August, 2025.
Repository Type: Research / Academic
This repository contains the research materials, code, and documentation for our thesis.
Our research evaluates how AI coding assistants influence software engineering outcomes in realistic full-stack development scenarios. Specifically, we compare Microsoft’s Phi-4 14B Reasoning Plus (a small language model) with Meta’s Llama-3.1 70B Instruct (a large language model), focusing on code quality, maintainability, performance, security, and developer productivity.
Unlike previous studies focused on isolated coding tasks, our work examines AI-assisted development in integrated MERN stack applications, reflecting real-world complexities.
Three open-source MERN stack projects:
| Category | Tool | Key Metrics |
|---|---|---|
| Reliability | SonarQube / ESLint | Bugs, Halstead Bugs, CLS |
| Maintainability | SonarQube / ESLint | Code Smells, Technical Debt, Cyclomatic Complexity, Halstead Effort |
| Hygiene | ESLint / Lighthouse | Total Issues, Best Practices |
| Performance | Lighthouse | INP, TBT, Performance Score |
| Security | OWASP ZAP | Detected vulnerabilities |
├── ProjectData/ # Data entry folder per project
├ └── *ProjectName*/
├ └── cli-gen-logs/ # Generation logs and output files
├ └── eslint-report/ # Contains all .json report output files and a .csv that includes them all
├ └── sonarqube/ # Contains an exported in .json version of the SonarQube project and a .csv with our selected metrics
└── README.md # This file
This repository is licensed under the MIT License, unless otherwise stated for third-party code or datasets.
- Georgios Panormitis Latos — [gusgeorgla@student.gu.se]
- Joey Karlsson — [gusjoeyka@student.gu.se]